“Moneyball” for Young Professionals

Last week the Fletcher Free Library and the UVM Humanities Center held a book club meeting at Centennial Field to discuss Moneyball by Michael Lewis. Moneyball has had such an enduring success it because it works on multiple levels. For one, it points us towards a new framework for understanding how baseball works. It also works as a story of a bunch of heroic underdogs who managed to wildly overachieve. But perhaps most intriguing, it works as a metaphor for we can rethink our own lives and careers.

The panel at the event included:

Bill “The Spaceman” Lee, Former MLB Pitcher

Beth Anderson, Burlington’s Chief Innovation Officer

Miro Weinberger, Mayor of Burlington

Tom Simon, Baseball historian and enthusiast

For those who haven’t read Moneyball, it chronicles the season of the 2002 Oakland Athletics and how they achieved great success with a miniscule budget of $44 million by using sophisticated data analysis, known in baseball as Sabermetrics, and questioning conventional wisdom.

Moneyball has had such an enduring success it because it works on multiple levels. For one, it points us towards a new framework for understanding how baseball works. It also works as a story of a bunch of heroic underdogs who managed to wildly overachieve. But perhaps most intriguing, it works as a metaphor for we can rethink our own lives and careers.

As I listened to the discussion, many interesting questions came up, often only superficially related to baseball. What are the unique statistics that underpin our own lives? In what ways could we benefit if we paid more attention to data? How do we make sure there’s meaning in what we’re measuring? How do we ensure that our search for data doesn’t overwhelm us with too much information?

One of the key themes discussed was how a Moneyball approach can be both very promising and very threatening. As Bill Lee pointed out, baseball functioned for a long time as an old boys club, which made it ripe for disruption and innovation. In a competitive environment, when one team is willing to use advanced analysis and another isn’t, it can be like shooting fish in a barrel.

While there are certainly limitations to this approach, as Tom Simon highlighted it’s not compelling to say, “Statistics is great and all, but what really matters is teamwork.” To that, the follow-up question of the statistician might be, “Then how do we quantify and analyze teamwork?” On the face of it, it sounds like a silly question, but what if we dig deeper and start defining teamwork? Simon suggested that we might understand teamwork as a function of three factors:

Players knowing their role

Players being content in their role

Players having confidence that their teammates will fulfill their roles

Looking at it this way, is it really that much of a stretch to think we can quantify teamwork and think of ways to improve it?

There are many sectors where one might draw parallels, but city government was at the forefront of the discussion in the room. Many governments have already signed onto the “Moneyball for Government” movement, which “encourages governments at all levels to increase their use of evidence and data when investing limited taxpayer dollars.[1]” But what does a Moneyball approach to city government look like?

Beth Anderson highlighted its potential for changing how we think about city planning and budgeting. For example, what if we better used infrastructure data to make our spending decisions? It’s often politically expedient to put off difficult spending decisions until something breaks down or a crisis emerges. A Moneyball approach, in this scenario, would be looking at the data and trying to address issues before things start breaking, and in doing so saving money in the long run.

An example raised by Miro Weinberger used data to make fire departments more efficient. This could mean sending out smaller fire trucks, looking into new equipment, streamlining inventory, and coming up with more ways to measure performance[2]. Of course, a cautious approach is sometimes called for, especially when people’s lives hinge on how you’ve structured your processes. It takes time and effort to gather data, and once you start gathering it, it can take time for trends and anomalies to emerge. Moneyball principles may not revolutionize the world today, but as time goes on and we continue gathering evidence about the way the world works I could see this approach paying huge dividends. In light of this, I think it’s worthwhile for everyone to consider how data gathering and analysis could transform their lives.

I’ll leave a word of caution though, for folks who might want to start measuring everything and everybody. As Bill Lee pointed out, the great managers are often the ones who don’t seem to do anything. To put it another way, part of being a great manager is putting in place a system that is able to smooth over friction on its own and doesn’t necessitate constant micromanaging. We’ve all seen politicians who seem to change their views every time a new poll comes out. I think it’s important to keep data in a proper perspective. If you’re not using it with a strong vision of what you want to achieve and trust in your teammates you might end up merely blowing with the wind.

Sure, it’s important to keep detailed statistics and look for ways to optimize them. But in the moment, when your next pitch could be the difference between going home and going to the World Series, all the statistics go out the window and the instinctual aspect of the game takes over. While the pitcher, the batter and the catcher are all being measured behind the scenes, that’s not their experience of the game.